Online self-help forums on cannabis: A content assessment

Using Social Media Data to Investigate Public Perceptions of Cannabis as a Medicine: Narrative Review

BACKGROUND

The use and acceptance of medicinal cannabis is on the rise across the globe. To support the interests of public health, evidence relating to its use, effects, and safety is required to match this community demand. Web-based user-generated data are often used by researchers and public health organizations for the investigation of consumer perceptions, market forces, population behaviors, and for pharmacoepidemiology.

OBJECTIVE

In this review, we aimed to summarize the findings of studies that have used user-generated text as a data source to study medicinal cannabis or the use of cannabis as medicine. Our objectives were to categorize the insights provided by social media research on cannabis as medicine and describe the role of social media for consumers using medicinal cannabis.

METHODS

The inclusion criteria for this review were primary research studies and reviews that reported on the analysis of web-based user-generated content on cannabis as medicine. The MEDLINE, Scopus, Web of Science, and Embase databases were searched from January 1974 to April 2022.

RESULTS

We examined 42 studies published in English and found that consumers value their ability to exchange experiences on the web and tend to rely on web-based information sources. Cannabis discussions have portrayed the substance as a safe and natural medicine to help with many health conditions including cancer, sleep disorders, chronic pain, opioid use disorders, headaches, asthma, bowel disease, anxiety, depression, and posttraumatic stress disorder. These discussions provide a rich resource for researchers to investigate medicinal cannabis-related consumer sentiment and experiences, including the opportunity to monitor cannabis effects and adverse events, given the anecdotal and often biased nature of the information is properly accounted for.

CONCLUSIONS

The extensive web-based presence of the cannabis industry coupled with the conversational nature of social media discourse results in rich but potentially biased information that is often not well-supported by scientific evidence. This review summarizes what social media is saying about the medicinal use of cannabis and discusses the challenges faced by health governance agencies and professionals to make use of web-based resources to both learn from medicinal cannabis users and provide factual, timely, and reliable evidence-based health information to consumers.

Social media discourse and internet search queries on cannabis as a medicine: A systematic scoping review

The use of cannabis for medicinal purposes has increased globally over the past decade since patient access to medicinal cannabis has been legislated across jurisdictions in Europe, the United Kingdom, the United States, Canada, and Australia. Yet, evidence relating to the effect of medical cannabis on the management of symptoms for a suite of conditions is only just emerging. Although there is considerable engagement from many stakeholders to add to the evidence base through randomized controlled trials, many gaps in the literature remain. Data from real-world and patient reported sources can provide opportunities to address this evidence deficit. This real-world data can be captured from a variety of sources such as found in routinely collected health care and health services records that include but are not limited to patient generated data from medical, administrative and claims data, patient reported data from surveys, wearable trackers, patient registries, and social media. In this systematic scoping review, we seek to understand the utility of online user generated text into the use of cannabis as a medicine. In this scoping review, we aimed to systematically search published literature to examine the extent, range, and nature of research that utilises user-generated content to examine to cannabis as a medicine. The objective of this methodological review is to synthesise primary research that uses social media discourse and internet search engine queries to answer the following questions: (i) In what way, is online user-generated text used as a data source in the investigation of cannabis as a medicine? (ii) What are the aims, data sources, methods, and research themes of studies using online user-generated text to discuss the medicinal use of cannabis. We conducted a manual search of primary research studies which used online user-generated text as a data source using the MEDLINE, Embase, Web of Science, and Scopus databases in October 2022. Editorials, letters, commentaries, surveys, protocols, and book chapters were excluded from the review. Forty-two studies were included in this review, twenty-two studies used manually labelled data, four studies used existing meta-data (Google trends/geo-location data), two studies used data that was manually coded using crowdsourcing services, and two used automated coding supplied by a social media analytics company, fifteen used computational methods for annotating data. Our review reflects a growing interest in the use of user-generated content for public health surveillance. It also demonstrates the need for the development of a systematic approach for evaluating the quality of social media studies and highlights the utility of automatic processing and computational methods (machine learning technologies) for large social media datasets. This systematic scoping review has shown that user-generated content as a data source for studying cannabis as a medicine provides another means to understand how cannabis is perceived and used in the community. As such, it provides another potential 'tool' with which to engage in pharmacovigilance of, not only cannabis as a medicine, but also other novel therapeutics as they enter the market.

Meeting the Unmet Needs of Individuals With Mental Disorders: Scoping Review on Peer-to-Peer Web-Based Interactions

BACKGROUND

An increasing number of online support groups are providing advice and information on topics related to mental health.

OBJECTIVE

This study aimed to investigate the needs that internet users meet through peer-to-peer interactions.

METHODS

A search of 4 databases was performed until August 15, 2022. Qualitative or mixed methods (ie, qualitative and quantitative) studies investigating interactions among internet users with mental disorders were included. The φ coefficient was used and machine learning techniques were applied to investigate the associations between the type of mental disorders and web-based interactions linked to seeking help or support.

RESULTS

Of the 13,098 identified records, 44 studies (analyzed in 54 study-disorder pairs) that assessed 82,091 users and 293,103 posts were included. The most frequent interactions were noted for people with eating disorders (14/54, 26%), depression (12/54, 22%), and psychoactive substance use disorders (9/54, 17%). We grouped interactions between users into 42 codes, with the empathy or compassion code being the most common (41/54, 76%). The most frequently coexisting codes were request for information and network (35 times; φ=0.5; P<.001). The algorithms that provided the best accuracy in classifying disorders by interactions were decision trees (44/54, 81%) and logistic regression (40/54, 74%). The included studies were of moderate quality.

CONCLUSIONS

People with mental disorders mostly use the internet to seek support, find answers to their questions, and chat. The results of this analysis should be interpreted as a proof of concept. More data on web-based interactions among these people might help apply machine learning methods to develop a tool that might facilitate screening or even support mental health assessment.

Consumer-Generated Discourse on Cannabis as a Medicine: Scoping Review of Techniques

BACKGROUND

Medicinal cannabis is increasingly being used for a variety of physical and mental health conditions. Social media and web-based health platforms provide valuable, real-time, and cost-effective surveillance resources for gleaning insights regarding individuals who use cannabis for medicinal purposes. This is particularly important considering that the evidence for the optimal use of medicinal cannabis is still emerging. Despite the web-based marketing of medicinal cannabis to consumers, currently, there is no robust regulatory framework to measure clinical health benefits or individual experiences of adverse events. In a previous study, we conducted a systematic scoping review of studies that contained themes of the medicinal use of cannabis and used data from social media and search engine results. This study analyzed the methodological approaches and limitations of these studies.

OBJECTIVE

We aimed to examine research approaches and study methodologies that use web-based user-generated text to study the use of cannabis as a medicine.

METHODS

We searched MEDLINE, Scopus, Web of Science, and Embase databases for primary studies in the English language from January 1974 to April 2022. Studies were included if they aimed to understand web-based user-generated text related to health conditions where cannabis is used as a medicine or where health was mentioned in general cannabis-related conversations.

RESULTS

We included 42 articles in this review. In these articles, Twitter was used 3 times more than other computer-generated sources, including Reddit, web-based forums, GoFundMe, YouTube, and Google Trends. Analytical methods included sentiment assessment, thematic analysis (manual and automatic), social network analysis, and geographic analysis.

CONCLUSIONS

This study is the first to review techniques used by research on consumer-generated text for understanding cannabis as a medicine. It is increasingly evident that consumer-generated data offer opportunities for a greater understanding of individual behavior and population health outcomes. However, research using these data has some limitations that include difficulties in establishing sample representativeness and a lack of methodological best practices. To address these limitations, deidentified annotated data sources should be made publicly available, researchers should determine the origins of posts (organizations, bots, power users, or ordinary individuals), and powerful analytical techniques should be used.

Evaluation of the Psychometric Properties of the Arab Compulsive Internet Use Scale (CIUS) by Item Response Theory Modeling (IRT)

INTRODUCTION

The psychometric properties of the Arab translation of the Compulsive Internet Use Scale (CIUS) have been previously studied by confirmatory factor analysis (CFA) with AMOS software using the asymptotically distribution-free (ADF) estimator. Unidimensionality has been achieved at the cost of correlating several item variance errors. However, several reviews of SEM software packages and estimation methods indicate that the option of robust standard errors is not present in the AMOS package and that ADF estimation may yield biased parameter estimates. We therefore explored a second analysis through item response theory (IRT) using the parametric graded response model (GRM) and the marginal maximum likelihood (MML) estimation method embedded in the LTM package of R software. Differential item functioning (DIF) or item bias across subpopulations was also explored within IRT framework as different samples were investigated. The objective of the current study is to (1) analyze the Arab CIUS scale with IRT, (2) investigate DIF in three samples, and (3) contribute to the ongoing debate on Internet-use-related addictive behaviors using the CIUS items as a proxy.

METHODS

We assessed three samples of people, one in Algeria and two in Lebanon, with a total of 1520 participants.

RESULTS

Almost three out of every five items were highly related to the latent construct. However, the unidimensionality hypothesis was not supported. Furthermore, besides being locally dependent, the scale may be weakened by DIF across geographic regions. Some of the CIUS items related to increasing priority, impaired control, continued use despite harm, and functional impairment as well as withdrawal and coping showed good discriminative capabilities. Those items were endorsed more frequently than other CIUS items in people with higher levels of addictive Internet use.

CONCLUSIONS

Contrary to earlier ADF estimation findings, unidimensionality of the CIUS scale was not supported by IRT parametric GRM in a large sample of Arab speaking participants. The results may be helpful for scale revision. By proxy, the study contributes to testing the validity of addiction criteria applied to Internet use related-addictive behaviors.

The complementary and substitutive value of online health information

The Internet plays a significant role in health information searching, sharing and emotional support. However, scholars have devoted little attention to the complementary and substitute value of online health information from diseases, especially chronic diseases, health insurance, barriers to health resources and their interaction effects with income. This research uses data from the 2020 Health Information National Trends Survey (HINTS 2020), the latest HINTS survey that includes seeking online health information questions critical to this research. This paper proposes that the factors contributing to seeking online health information can be categorized into two modalities - complementary and substitutive. Concerning the complementary value, I argue that individuals with certain health conditions use online health information as a complementary health resource in addition to traditional health resources such as doctors to understand their health issues better. Online health information also functions as substitute information sources for individuals who have experienced more barriers to typical health information resources.

Des repères pour la conception des apps ?

Objectif Proposer quelques repères pour faciliter le processus de création d’applications pour téléphones intelligents (apps) en santé mentale.

Méthode Présentation brève de l’intérêt potentiel des apps et proposition argumentée d’étapes clés pour la création des apps. L’article se base sur une revue narrative, un retour d’expérience et des discussions de groupes d’experts.

Résultats Les apps ont des caractéristiques ubiquitaires particulièrement intéressantes pour le domaine de la santé mentale. Potentiellement connectées à de multiples technologies, mobiles et disponibles en tout temps, elles permettent une grande flexibilité de conception. Afin d’augmenter les chances d’efficacité et de bonne dissémination d’une app donnée, certains principes pourraient guider de manière utile le travail de conception des apps : 9 repères sont proposés, en particulier une bonne intégration des utilisateurs finaux autour d’objectifs cibles bien définis durant tout le processus de création de tels outils.

Conclusion Les repères proposés pourraient faciliter le processus de création d’apps pour la santé mentale.

Compulsive Health-Related Internet Use and Cyberchondria

BACKGROUND

Cyberchondria denotes excessive and repeated online health-related searches associated with an increase in health anxiety. Such searches persist in those with cyberchondria, despite the negative consequences, resembling a pattern of compulsive Internet use.

OBJECTIVES

The aim of the present study was to assess compulsive health-related Internet use in relation to cyberchondria while controlling for related variables.

METHOD

Adult participants (N = 749) were recruited from an online platform. They completed questionnaires assessing the severity of cyberchondria (via the Cyberchondria Severity Scale [CSS]), compulsive Internet use adapted for online health-related seeking (via the adapted Compulsive Internet Use Scale [CIUS]), and levels of intolerance of uncertainty and anxiety, as well as depressive, somatic, and obsessive-compulsive symptoms. A logistic regression analysis was carried out to identify predictors of scores above a cutoff value on the CIUS, indicating compulsive health-related Internet use.

RESULTS

The regression output showed that only the CSS total score and sex made a unique, statistically significant contribution to the model, leading to the correct classification of 78.6% of the cases. Of the CSS subscales, compulsion and distress were the most strongly associated with compulsive health-related Internet use.

CONCLUSIONS

The finding that the adapted CIUS scores are associated with cyberchondria indicates that cyberchondria has a compulsive component, at least in terms of health-related Internet use. It also suggests that compulsive health-related Internet use persists despite the distress associated with this activity. Males may engage in cyberchondria more compulsively than females. These findings have implications for research and clinical practice.

Evaluating the Communication of Online Social Support: A Mixed-Methods Analysis of Structure and Content

Social support in online self-help groups has been found to benefit participants with emotional instability or mental illness. Many studies have employed content analysis to reveal categories of social support, claiming the prevalence of emotional and informational support can aid support seekers. In the studies, optimal matching theory is used to explain the helpfulness of these types of support. This article argues that content analysis is unpersuasive in its claim that support seekers benefit from social support; participants' communicative behaviors should also be considered to evaluate the potential advantages and drawbacks of such groups. Drawing on a mixed-method approach of conversation analysis and content analysis, this study investigates the sequential structure and content of social support in communication in six online self-help groups for anxiety and depression (OSGADs). The main findings show that optimal matching theory may not be suitable for elucidating how support seekers receive help due to the immediate provision of social support and little interaction otherwise. In addition, results identify expressed understanding/empathy and advice as prominent support categories in OSGADs, with most thread openers requesting support indirectly.

Social Connection and Online Engagement: Insights From Interviews With Users of a Mental Health Online Forum

BACKGROUND

Over the past 2 decades, online forums for mental health support have emerged as an important tool for improving mental health and well-being. There has been important research that analyzes the content of forum posts, studies on how and why individuals engage with forums, and how extensively forums are used. However, we still lack insights into key questions on how they are experienced from the perspective of their users, especially those in rural and remote settings.

OBJECTIVE

The aim of our study was to investigate the dynamics, benefits, and challenges of a generalized peer-to-peer mental health online forum from a user perspective; in particular, to better explore and understand user perspectives on connection, engagement, and support offered in such forums; information and advice they gained; and what issues they encountered. We studied experiences of the forums from the perspective of both people with lived experience of mental illness and people who care for people with mental illness.

METHODS

To understand the experience of forum users, we devised a qualitative study utilizing semistructured interviews with 17 participants (12 women and 5 men). Data were transcribed, and a thematic analysis was undertaken.

RESULTS

The study identified 3 key themes: participants experienced considerable social and geographical isolation, which the forums helped to address; participants sought out the forums to find a social connection that was lacking in their everyday lives; and participants used the forums to both find and provide information and practical advice.

CONCLUSIONS

The study suggests that online peer support provides a critical, ongoing role in providing social connection for people with a lived experience of mental ill-health and their carers, especially for those living in rural and remote areas. Forums may offer a way for individuals to develop their own understanding of recovery through reflecting on the recovery experiences and peer support shown by others and individuals enacting peer support themselves. Key to the success of this online forum was the availability of appropriate moderation, professional support, and advice.

Sexual Desire, Mood, Attachment Style, Impulsivity, and Self-Esteem as Predictive Factors for Addictive Cybersex

BACKGROUND

An increasing number of studies are concerned with various aspects of cybersex addiction, the difficulty some persons have in limiting cybersex use despite a negative impact on everyday life.

OBJECTIVE

The aim of this study was to assess potential links between the outcome variable cybersex addiction, assessed with the Compulsive Internet Use Scale (CIUS) adapted for cybersex use, and several psychological and psychopathological factors, including sexual desire, mood, attachment style, impulsivity, and self-esteem, by taking into account the age, sex, and sexual orientation of cybersex users.

METHODS

A Web-based survey was conducted in which participants were assessed for sociodemographic variables and with the following instruments: CIUS adapted for cybersex use, Sexual Desire Inventory, and Short Depression-Happiness Scale. Moreover, attachment style was assessed with the Experiences in Close Relationships-Revised questionnaire (Anxiety and Avoidance subscales). Impulsivity was measured by using the Urgency, Premeditation (lack of), Perseverance (lack of), Sensation Seeking, Positive Urgency Impulsive Behavior Scale. Global self-esteem was assessed with the 1-item Self-Esteem Scale.

RESULTS

A sample of 145 subjects completed the study. Addictive cybersex use was associated with higher levels of sexual desire, depressive mood, avoidant attachment style, and male gender but not with impulsivity.

CONCLUSIONS

Addictive cybersex use is a function of sexual desire, depressive mood, and avoidant attachment.